Schwark, FenjaGarmatter, HenrietteDavila, MariaDawel, LisaPehlken, AlexandraCyris, FabianScharf, RolandWohlgemuth, VolkerNaumann, StefanArndt, Hans-KnudBehrens, GritHöb, Maximilian2022-09-192022-09-192022978-3-88579-722-7https://dl.gi.de/handle/20.500.12116/39413In this paper, we present an image recognition method to improve the performance of waste-to-energy plants. Thermal treatment of waste in waste-to-energy plants is central for the treatment of municipal solid waste. The heterogeneous nature of municipal solid waste results in a fluctuating lower calorific value to which plant operation must be adapted. Compensating for drastic changes in the lower calorific value is challenging for plant operation and can require short-term interventions. Estimating the lower calorific value prior to the combustion process should reduce the number of short-term interventions. In this work, we propose a process-engineering approach to estimate the lower calorific value of waste as a new application of image recognition in waste-to-energy plants. The method is implemented using videos and sensor data from a case study in a real waste-to-energy plant in Germany.enwaste-to-energyimage recognitionwaste propertiesprocess modelingText/Conference Paper1617-5468